Blockchain-Driven AI-Enhanced Post-Quantum Multivariate Identity-based Signature and Privacy-Preserving Data Aggregation Scheme for Fog-enabled Flying Ad-Hoc Networks

Computer Science > Cryptography and Security [Submitted on 20 Apr 2026] Blockchain-Driven AI-Enhanced Post-Quantum Multivariate Identity-based Signature and Privacy-Preserving Data Aggregation Scheme for Fog-enabled Flying Ad-Hoc Networks Sufian Al majmaie, Ghazal Ghajari, Niraj Prasad Bhatta, Fathi Amsaad The integration of Fog Computing with Flying Ad-Hoc Networks (FANETs) offers promising capabilities for decentralized, low-latency intelligence in UAV-based applications. However, the distributed nature, mobility, and resource constraints of FANETs expose them to significant security and privacy challenges, particularly against quantum threats. To address these issues, this work introduces a blockchain-based, AI-enhanced key management framework designed for fog-enabled FANETs. The proposed scheme employs a Post-Quantum Multivariate Identity-Based Signature Scheme (PQ-MISS) and Zero-Knowledge Proofs (ZKPs) to achieve secure key establishment, privacy-preserving data aggregation, and integrity verification. A polynomial composition-based encryption mechanism and an aggregate signature model support secure and efficient multi-device communication across fog and UAV layers. Fog servers construct partial blockchain blocks from validated UAV data. These blocks are completed and mined by Cloud Servers (CSs). AI algorithms then analyze the verified data to generate accurate predictions and insights. NS-3 simulations validate the efficiency of PQ-MISS in reducing communication overhead while improving the speed and reliability of data aggregation and verification. Comparative analysis demonstrates the proposed scheme's advantages over existing methods in computational cost, post-quantum security, and scalability, making it a robust solution for secure, intelligent, and future-ready FANET systems. Subjects: Cryptography and Security (cs.CR) Cite as: arXiv:2604.18819 [cs.CR]   (or arXiv:2604.18819v1 [cs.CR] for this version)   https://doi.org/10.48550/arXiv.2604.18819 Focus to learn more Submission history From: Ghazal Ghajari [view email] [v1] Mon, 20 Apr 2026 20:40:55 UTC (1,241 KB) Access Paper: HTML (experimental) view license Current browse context: cs.CR < prev   |   next > new | recent | 2026-04 Change to browse by: cs References & Citations NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)